Objective: Develop a template to understand the intricacies of our data, starting with Excel files, to provide meaningful insights for business analysts and data engineers. This template should guide the data profiling process, ensuring that the most relevant information is captured to support data quality and decision-making.
Questions to Explore:
- What types of profiling data (e.g., missing values, data types, formulas, and inconsistencies) are important for understanding the content and quality of Excel files?
- How can we capture these data points in a structured and consistent way to help identify patterns, anomalies, and areas requiring further attention?
- What should the template include to provide actionable insights for business analysts and ensure seamless collaboration with data engineers?
Objective: Develop a template to understand the intricacies of our data, starting with Excel files, to provide meaningful insights for business analysts and data engineers. This template should guide the data profiling process, ensuring that the most relevant information is captured to support data quality and decision-making.
Questions to Explore:
- What types of profiling data (e.g., missing values, data types, formulas, and inconsistencies) are important for understanding the content and quality of Excel files?
- How can we capture these data points in a structured and consistent way to help identify patterns, anomalies, and areas requiring further attention?
- What should the template include to provide actionable insights for business analysts and ensure seamless collaboration with data engineers?